Weaving sections may cause massive congestion and accident problems. Connected and automated vehicles (CAVs) are acknowledged to improve traffic safety and efficiency through effective communication and control. To this end, this study proposes a centralized cooperative vehicle trajectory planning framework for SAE Level 4 or 5 automation. Specifically, focusing on the complex movements at weaving sections, the longitudinal optimal trajectory control is proposed to avoid collisions. This improves traffic efficiency and reduces fuel consumption and driver discomfort. A sideswipe collision prediction algorithm takes into account the geometric features of vehicles and predicts the time of the collision. The merging sequences model with safety constraints is developed to avoid the collision between the on-ramp and off-ramp vehicles. The effectiveness of the proposed model is validated through simulations, where the proposed method is compared with the baseline to demonstrate its potential in improving safety and reducing the fuel consumption and travel time.

编织部分可能会导致严重的拥堵和事故问题。互联和自动驾驶汽车（CAV）被公认为通过有效的通信和控制来提高交通安全性和效率。为此，本研究提出了用于SAE 4级或5级自动化的集中式协作车辆轨迹规划框架。具体而言，针对织造部分的复杂运动，提出了纵向最佳轨迹控制以避免碰撞。这提高了交通效率并减少了油耗和驾驶员不适感。侧滑碰撞预测算法考虑了车辆的几何特征并预测了碰撞时间。建立了具有安全约束的合并序列模型，以避免匝道车辆与匝道车辆之间发生碰撞。